UGC NET JRF November 2020 Paper-2
October 12, 2023Digital-Logic-Design
October 12, 2023UGC NET JRF November 2020 Paper-2
| Question 22 |
The process of removing details from a given state representative is called___.
| Extraction | |
| Mining | |
| Selection | |
| Abstraction |
Question 22 Explanation:
Abstraction: the process of removing physical, spatial, or temporal details or attributes in the study of objects or systems to focus attention on details of greater importance; it is similar in nature to the process of generalization.
Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration).
Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration).
Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
Correct Answer: D
Question 22 Explanation:
Abstraction: the process of removing physical, spatial, or temporal details or attributes in the study of objects or systems to focus attention on details of greater importance; it is similar in nature to the process of generalization.
Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration).
Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration).
Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
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